Curvelet Transform and Hybrid Bacterial Foraging Optimization for Image Denoising

Eliminating noise from the original image is still a challenging task for researchers. Several algorithms have been proposed and each of them has its own assumptions, advantages & limitations. The paper proposes the noise reduction method for the medical images by using Hybrid BFO i.e the fusion of BFO (Bacteria foraging optimization) and the technique of contourlet transform and the results are compared with the older technique of image denoising using curvelet transform. BFO algorithm is an artificial intelligence nature-inspired optimization algorithm technique which is based on mimicking the foraging behavior of E.coli bacteria and it is now applied to the field of imagingdenosing.